Post-COVID-19 Electrophysiological, Cognitive and Psychological Assessment in a Sample of Healthcare Providers in Qena Governorate
Bibliographic record
Abstract
Background: The COVID-19 outbreak threatens society globally. Stress and depression are common. Electrophysiological, cognitive, psychological, and covid-19 disease assessmentsObjectives: Assessment relationship between cognition, psychological and covid-19 disease.Patients and methods: 30 patients had covid-19-positive PCR, and 25 healthy controls matched for Sex and Age. Electroencephalogram (EEG) assessed electrophysiological changes, cognitive functions were assessed using Trail Making Test (parts A and B) and Montreal Cognitive Assessment (MoCA), depression and anxiety were assessed using HAM D & A.Results: No EEG changes after 1 month between cases and controls (p-value=0.099) and after 3 months (p-value=0.293).Follow, neither cases nor controls has EEG changes(p-value=0.630,1.0).Cases and controls differ in trail A(p-value=0.003) after month while after 3 months(p-value=0.123). In the cases, trail A after 1 month is different from trail A after 3 months(p-value=0.001). In controls, trail A after 1 month and 3 months is identical(p-value=0.428). Trail B shows no significant difference between cases and controls after 1 and 3 months(p-value=0.170,0.428)Cases and controls differ in 1-month MoCA(p-value=0.001). Cases and controls have similar MoCA after 3 months (p-value=0.917). Repeat MoCA after 3 months differs statistically(p-value=0.001,0.896). HAM-A statistically differs between cases and controls after 1 month(p-value=0.005), but not after 3 months(p-value=0.133). Cases and controls differ for HAM A within 1 month and after 3 months (p-value=0.001,0.048). After 1 month, HAM D cases and controls differ (p-value=0.249,0.753).follow cases and controls identical (p-value=0.006,0.188)Conclusion: Our study shows that SARS-CoV-2 impairs healthcare workers cognition and psyche.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".